To deal with the problem in emergency plan matching of highway traffic that incident description is incomplete, incident properties are unclear, and plan matching is inaccurate, etc., a plan matching method is proposed based on fuzzy sets and rough sets. The property weight calculation method based on rough sets is used to reduce the dependency on prior knowledge; the structural similarity calc...

It goes without saying that a challenging quest for the construction of intelligent systems is realized through the development of hybrid information technologies and their vigorous and prudent exploitation. In a nutshell, what has emerged under the name of computational intelligence (CI) or soft computing is a well-orchestrated, highly synergistic consortium of technologies of neural networks,...

Consensus is defined as a cooperative process in which a group of decision makers develops and agrees to support a decision in the best interest of the whole. It is a questioning process, more than an affirming process, in which the group members usually modify their choices until a high level of agreement within the group is achieved. Given the importance of forming an accepted decision by the...

Based on the observation that rough sets and mathematical morphology are both using dual operators sharing similar properties, we investigate more closely the links existing between both the domains. We establish the equivalence between some morphological operators and rough sets de"ned from either a relation, or a pair of dual operators or a neighborhood system. Then we suggest some extensions...

This paper generalizes the concepts of rough membership functions in pattern classification tasks to fuzz rough membership functions. Unlike the rough membersgp value of a pattern, which is sensitive only towards the rough uncertainty associated with the pattern, the fuzzy-rough membership value of the pattern signlfies the rou h uncertainty as well as the . fuzz uncertainty associated wig it. ...

A conjunction T ties an implication operator A if the identity A(a,A(b, z)) = A(T (a, b), z) holds [A.A. Abdel-Hamid, N.N. Morsi, Associatively tied implications, Fuzzy Sets and Systems 136 (2003) 291–311]. We study the class of tied adjointness algebras (which are five-connective algebras on two partially ordered sets), in which the implications are tied by triangular norms. This class contain...

This paper presents a methodology to biological image classification through a Rough-Fuzzy Artificial Neural Network (RFANN). This approach is used in order to improve the learning process by Rough Sets Theory (RS) focusing on the feature selection, considering that the RS feature selection allows the use of low dimension features from the image database. This result could be achieved, once the...

The paper presents a transition from the crisp rough set theory to a fuzzy one, called Alpha Rough Set Theory or, in short, a-RST. All basic concepts or rough set theory are extended, i.e., information system, indiscernibility, dependency, reduction, core, de®nability, approximations and boundary. The resulted theory takes into account fuzzy data and allows the approximation of fuzzy concepts. ...

As medical images contain uncertainties, there are difficulties in classification of images into homogeneous regions. Fuzzy sets, rough sets and the combination of fuzzy and rough sets plays a prominent role in formalizing uncertainty, vagueness, and incompleteness in diagnosis. Development of hybrid approaches for the segmentation of the magnetic resonance imaging (MRI) with the ability of com...